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Record W4315619872 · doi:10.1001/jamasurg.2022.6855

Effect of High-Dose Selenium on Postoperative Organ Dysfunction and Mortality in Cardiac Surgery Patients

2023· article· en· W4315619872 on OpenAlexaffabout
Christian Stoppe, Bernard McDonald, Patrick Meybohm, Kenneth B. Christopher, Stephen E. Fremes, Richard Whitlock, Siamak Mohammadi, Dimitri Kalavrouziotis, Gunnar Elke, Rolf Rossaint, Philipp Helmer, Kai Zacharowski, Ulf Günther, Matteo Parotto, Bernd Niemann, Andreas Böning, C. David Mazer, Philip M. Jones, Marion Ferner, Yoan Lamarche, François Lamontagne, Oliver J. Liakopoulos, Matthew Cameron, Matthias Müller, Alexander Zarbock, Mária Wittmann, Andreas Goetzenich, Erich Kilger, Lutz Schomburg, Andrew G. Day, Daren K. Heyland, Gregory M. T. Hare, M. Chu, Pierre Voisine, François Dagenais, Éric Dumont, Frédérique Jacques, Éric Charbonneau, Jean Perron, Simone Lindau, Roupen Hatzakorizan, Assad Haneya, Georg Trummer, Angela Jareth, Xuran Jiang, Ellen Dresen, Aileen Hill

Bibliographic record

VenueJAMA Surgery · 2023
Typearticle
Languageen
FieldNursing
TopicSelenium in Biological Systems
Canadian institutionsClinical Evaluation Research UnitMontreal Heart InstituteLondon Health Sciences CentreUniversity of OttawaHôpital du Sacré-Cœur de MontréalJewish General HospitalSt. Michael's HospitalToronto General HospitalHamilton Health SciencesUniversity of TorontoHôpital FleurimontQueen's UniversitySunnybrook HospitalUniversité Laval
Fundersnot available
KeywordsMedicineOrgan dysfunctionCardiac surgerySeleniumSurgeryInternal medicineSepsis

Abstract

fetched live from OpenAlex

Importance: Selenium contributes to antioxidative, anti-inflammatory, and immunomodulatory pathways, which may improve outcomes in patients at high risk of organ dysfunctions after cardiac surgery. Objective: To assess the ability of high-dose intravenous sodium selenite treatment to reduce postoperative organ dysfunction and mortality in cardiac surgery patients. Design, Setting, and Participants: This multicenter, randomized, double-blind, placebo-controlled trial took place at 23 sites in Germany and Canada from January 2015 to January 2021. Adult cardiac surgery patients with a European System for Cardiac Operative Risk Evaluation II score-predicted mortality of 5% or more or planned combined surgical procedures were randomized. Interventions: Patients were randomly assigned (1:1) by a web-based system to receive either perioperative intravenous high-dose selenium supplementation of 2000 μg/L of sodium selenite prior to cardiopulmonary bypass, 2000 μg/L immediately postoperatively, and 1000 μg/L each day in intensive care for a maximum of 10 days or placebo. Main Outcomes and Measures: The primary end point was a composite of the numbers of days alive and free from organ dysfunction during the first 30 days following cardiac surgery. Results: A total of 1416 adult cardiac surgery patients were analyzed (mean [SD] age, 68.2 [10.4] years; 1043 [74.8%] male). The median (IQR) predicted 30-day mortality by European System for Cardiac Operative Risk Evaluation II score was 8.7% (5.6%-14.9%), and most patients had combined coronary revascularization and valvular procedures. Selenium did not increase the number of persistent organ dysfunction-free and alive days over the first 30 postoperative days (median [IQR], 29 [28-30] vs 29 [28-30]; P = .45). The 30-day mortality rates were 4.2% in the selenium and 5.0% in the placebo group (odds ratio, 0.82; 95% CI, 0.50-1.36; P = .44). Safety outcomes did not differ between the groups. Conclusions and Relevance: In high-risk cardiac surgery patients, perioperative administration of high-dose intravenous sodium selenite did not reduce morbidity or mortality. The present data do not support the routine perioperative use of selenium for patients undergoing cardiac surgery. Trial Registration: ClinicalTrials.gov Identifier: NCT02002247.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Randomized trial · Consensus signal: Randomized trial
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.018
GPT teacher head0.258
Teacher spread0.240 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designRandomized trial
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations40
Published2023
Admission routes2
Has abstractyes

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